Western OC2 Lab

AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Intrusion-Detection-System-Using-Machine-Learning

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

PWPAE-Concept-Drift-Detection-and-Adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.

Intrusion-Detection-System-Using-CNN-and-Transfer-Learning

Code for intrusion detection system (IDS) development using CNN models and transfer learning

Vibration-Based-Fault-Diagnosis-with-Low-Delay

Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

OASW-Concept-Drift-Detection-and-Adaptation

An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.

MSANA-Online-Data-Stream-Analytics-And-Concept-Drift-Adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.

FL-IOV-ITS

Code for the case study presented in "Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems" accepted for publication in the IEEE Network Magazine May 2021 Special Issue on AI-empowered Mobile Edge Computing in the Internet of Vehicles.

AutoML-and-Adversarial-Attack-Defense-for-Zero-Touch-Network-Security

This repository includes code for the AutoML-based IDS and adversarial attack defense case studies presented in the paper "Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis" published in IEEE Transactions on Network and Service Management.

5G-Core-Networks-Datasets

Student-Performance-and-Engagement-Prediction-eLearning-datasets

This repository contains the datasets used as part of the OC2 lab's work on Student Performance prediction and student engagement prediction in eLearning environments using machine learning methods.

Wireless-Resource-Virtualization-with-Device-to-Device-Communication-Underlaying-LTE-Networks

Implementation of Wireless Resource Virtualization with Device-to-Device Communication Underlaying LTE Networks

Similarity-Based-Predictive-Maintenance-Framework-for-Rotating-Machinery

Python code “Jupyter notebooks” for the paper entitled " Similarity-Based Predictive Maintenance Framework for Rotating Machinery" has been presented in the Fifth International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22), Cairo, Egypt, 27-29 December 2022. Techniques used: statistical analysis, FFT, and STFT.

Signal-Processing-for-Machine-Learning

This repository serves as a platform for posting a diverse collection of Python codes for signal processing, facilitating various operations within a typical signal processing pipeline (pre-processing, processing, and application).

Data-driven-Methods-for-the-Reduction-of-Energy-Consumption-in-Warehouses-Use-Case

This is the repository that includes the code of the use case in the paper titled "Data-driven Methods for the Reduction of Energy Consumption in Warehouses: Use-Case Driven Analysis"

SB-PdM-a-tool-for-predictive-maintenance-of-rolling-bearings-based-on-limited-labeled-data

SB-PdM is a non-machine learning code to perform Predictive Maintenance (PdM) of rolling bearings without the need to train a classifier. In SM-PdM, the classification task is performed by applying a similarity measure between test sample and class-reference labeled samples in the feature space.

CorrFL

This repository includes the code used in the paper titled "CorrFL: Correlation-based Neural Network Architecture for Unavailability Concerns in a Heterogeneous IoT Environment"

DNS_Typosquatting_Detection_Datasets

This repository contains the datasets used as part of the OC2 lab's work on DNS Typosquatting Detection using machine learning methods

hierarchical-CO2

This is a repository that includes the code used in the paper titled "Hierarchical Modelling for CO2 Variation Prediction for HVAC System Operation"

Hyperparameter-Optimization-of-Machine-Learning-Algorithms

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

IntelligentAQM

Intelligent method to be used with AQM schemes such as CoDel and FQ-CoDel

TinyML_EVCI

This repository contains code for comparing traditional Machine Learning (ML) and Tiny Machine Learning (TinyML) in terms of time, memory usage, and performance, specifically in the context of electric vehicle charging infrastructure. It also offers practical insights by implementing TinyML on the ESP32 microcontroller.

Zero-Touch-Network-and-AutoML-Case-Study

This repository includes code for the AutoML-based case study for zero-touch networks presented in the paper "Zero-touch networks: Towards next-generation network automation" published in Computer Networks (IF:5.6).